Date of Award

Spring 2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Ocean & Earth Sciences

Program/Concentration

Oceanography

Committee Director

John Klinck

Committee Member

Cynthia Jones

Committee Member

Norou Diawara

Committee Member

Kent Carpenter

Abstract

The ability to assign accurate ages of fish is important to fisheries management. Accurate ageing allows for the most reliable age-based models to be used to support sustainability and maximize economic benefit. Structures used to age include bones, scales, and most commonly ear bones (otoliths). Assigning age relies on validating putative annual marks by evaluating accretional material laid down in patterns in fish otoliths, typically by marginal increment analysis. These patterns often take the shape of a sawtooth wave with an abrupt drop in accretion yearly to form an annual band and are typically validated qualitatively. Researchers have shown keen interest in modeling marginal increments to verify the marks do, in fact, occur yearly. However, it has been challenging in finding the best model to predict this sawtooth wave pattern. I propose three new applications of time series models to validate the existence of the yearly sawtooth wave patterned data: autoregressive integrated moving average (ARIMA), unobserved components model (UCM) and copula. These methods are expected to enable the identification of yearly patterns in accretion. ARIMA and UCM account for the dependence of observations and error, while copula incorporates a variety of marginal distributions and dependence structure. Results indicate that all three models are valid to predict annuli formation. ARIMA works best with a sharp, distinct sawtooth wave while copula is best for data without the sharp drop

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DOI

10.25777/xtd6-g229

ISBN

9798382770826

ORCID

0009-0009-1484-5390

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